{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "37f162e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>数据时间</th>\n",
       "      <th>总有功功率（kw）</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018/1/1 0:00</td>\n",
       "      <td>244033.7682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018/1/1 0:15</td>\n",
       "      <td>232720.6402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018/1/1 0:30</td>\n",
       "      <td>231685.6891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018/1/1 0:45</td>\n",
       "      <td>227581.3317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018/1/1 1:00</td>\n",
       "      <td>233482.4269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128151</th>\n",
       "      <td>2021/8/31 22:45</td>\n",
       "      <td>202409.1270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128152</th>\n",
       "      <td>2021/8/31 23:00</td>\n",
       "      <td>218576.4635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128153</th>\n",
       "      <td>2021/8/31 23:15</td>\n",
       "      <td>200112.5091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128154</th>\n",
       "      <td>2021/8/31 23:30</td>\n",
       "      <td>199865.5937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128155</th>\n",
       "      <td>2021/8/31 23:45</td>\n",
       "      <td>198483.5592</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>128156 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   数据时间    总有功功率（kw）\n",
       "0         2018/1/1 0:00  244033.7682\n",
       "1         2018/1/1 0:15  232720.6402\n",
       "2         2018/1/1 0:30  231685.6891\n",
       "3         2018/1/1 0:45  227581.3317\n",
       "4         2018/1/1 1:00  233482.4269\n",
       "...                 ...          ...\n",
       "128151  2021/8/31 22:45  202409.1270\n",
       "128152  2021/8/31 23:00  218576.4635\n",
       "128153  2021/8/31 23:15  200112.5091\n",
       "128154  2021/8/31 23:30  199865.5937\n",
       "128155  2021/8/31 23:45  198483.5592\n",
       "\n",
       "[128156 rows x 2 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "#设置绘图时显示的中文字体\n",
    "plt.rcParams['font.sans-serif']=['Microsoft YaHei']\n",
    "power_info=pd.read_csv('td01.csv')\n",
    "power_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d81a5c17",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "128544\n",
      "128156\n"
     ]
    }
   ],
   "source": [
    "std_rng=pd.date_range(start='2018/1/1 0:00',end='2021/8/31 23:45',freq='15min')\n",
    "print(len(std_rng))\n",
    "print(len(power_info))#检查时间序列是否完整"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5e1e6eed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "128544\n"
     ]
    }
   ],
   "source": [
    "power_info = power_info.set_index(pd.to_datetime(power_info['数据时间'])).drop('数据时间',axis=1)\n",
    "power_info = power_info.resample('D').mean().interpolate()\n",
    "print(len(power_info))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8a908549",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8f41fefb50>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "findfont: Font family ['sans-serif'] not found. Falling back to DejaVu Sans.\n",
      "findfont: Generic family 'sans-serif' not found because none of the following families were found: Microsoft YaHei\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1123.2x518.4 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#预览数据\n",
    "fig=plt.figure(figsize=(15.6,7.2))\n",
    "ax=fig.add_subplot(111)\n",
    "line=ax.plot(power_info.index,power_info['总有功功率（kw）'],\\\n",
    "             'r-',label='power')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1833d734",
   "metadata": {},
   "outputs": [],
   "source": [
    "#使用拉格朗日插值函数对异常值插值\n",
    "from scipy.interpolate import lagrange#导入插值函数\n",
    "def inmsg(s,label_index,k=5):\n",
    "    sc=s.copy()\n",
    "    #获取标签索引位置\n",
    "    loc=sc.index.get_loc(label_index)\n",
    "    stmp=sc[loc-k:loc+k+1]\n",
    "    #生成插值序列\n",
    "    x=list(range(0,k))+list(range(k+1,2*k+1))\n",
    "    stmp=list(stmp[0:k])+list(stmp[k+1:2*k+1])\n",
    "    #插值\n",
    "    ret=lagrange(x,stmp)(k)\n",
    "    #将插值结果赋回原序列\n",
    "    sc[label_index]=ret\n",
    "    return sc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fa9a5ad2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#使用inmsg()对负荷小于10000的异常点进行插值\n",
    "intrp_label=power_info['总有功功率（kw）'][power_info['总有功功率（kw）']<10000].index\n",
    "for label_index in intrp_label:\n",
    "    power_info['总有功功率（kw）']=inmsg(power_info['总有功功率（kw）'],label_index,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4d3b7ecc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8f494cd5b0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1123.2x518.4 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#预览数据\n",
    "fig=plt.figure(figsize=(15.6,7.2))\n",
    "ax=fig.add_subplot(111)\n",
    "line=ax.plot(power_info.index,power_info['总有功功率（kw）'],\\\n",
    "             'r-',label='power')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b6a87e18",
   "metadata": {},
   "outputs": [],
   "source": [
    "#输出数据\n",
    "column=['数据时间','总有功功率（kw）']\n",
    "td01_new=pd.DataFrame(columns=column,data=power_info)\n",
    "td01_new.to_csv('td01_new.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "37e04e3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>总有功功率（kw）</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>数据时间</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-01 00:00:00</th>\n",
       "      <td>244033.7682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 00:15:00</th>\n",
       "      <td>232720.6402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 00:30:00</th>\n",
       "      <td>231685.6891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 00:45:00</th>\n",
       "      <td>227581.3317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01 01:00:00</th>\n",
       "      <td>233482.4269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31 22:45:00</th>\n",
       "      <td>202409.1270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31 23:00:00</th>\n",
       "      <td>218576.4635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31 23:15:00</th>\n",
       "      <td>200112.5091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31 23:30:00</th>\n",
       "      <td>199865.5937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31 23:45:00</th>\n",
       "      <td>198483.5592</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>128544 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       总有功功率（kw）\n",
       "数据时间                            \n",
       "2018-01-01 00:00:00  244033.7682\n",
       "2018-01-01 00:15:00  232720.6402\n",
       "2018-01-01 00:30:00  231685.6891\n",
       "2018-01-01 00:45:00  227581.3317\n",
       "2018-01-01 01:00:00  233482.4269\n",
       "...                          ...\n",
       "2021-08-31 22:45:00  202409.1270\n",
       "2021-08-31 23:00:00  218576.4635\n",
       "2021-08-31 23:15:00  200112.5091\n",
       "2021-08-31 23:30:00  199865.5937\n",
       "2021-08-31 23:45:00  198483.5592\n",
       "\n",
       "[128544 rows x 1 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "power_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5f0bf38",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
